Florent Masseglia
111
Documents
Publications
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A One-Health Platform for Antimicrobial Resistance Data AnalyticsCIKM 2024 - 33rd ACM International Conference on Information and Knowledge Management, Oct 2024, Boise, United States. ⟨10.1145/3627673.3679237⟩
Conference papers
lirmm-04774438v1
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Parallel Techniques for Variable Size Segmentation of Time Series DatasetsADBIS 2022 - 26th European Conference on Advances in Databases and Information Systems, Sep 2022, Turin, Italy. pp.148-162, ⟨10.1007/978-3-031-15740-0_12⟩
Conference papers
lirmm-03805997v1
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Variable size segmentation for efficient representation and querying of non-uniform time series datasetsSAC 2022 - 37th ACM/SIGAPP Symposium on Applied Computing, Apr 2022, Virtual Event, United States. pp.395-402, ⟨10.1145/3477314.3507000⟩
Conference papers
lirmm-03806053v1
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ASAX : Segmentation adaptative basée sur la quantité d'information pour SAXBDA 2021 - 37e Conférence sur la Gestion de Données - Principes, Technologies et Applications, Oct 2021, Paris, France
Conference papers
lirmm-03468535v1
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Massively Distributed Clustering via Dirichlet Process MixtureECML PKDD 2020 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Sep 2020, Ghent / Virtual, Belgium. ⟨10.1007/978-3-030-67670-4_34⟩
Conference papers
lirmm-03036910v1
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High Dimensional Data Clustering by means of Distributed Dirichlet Process Mixture ModelsIEEE Big Data 2019 - IEEE International Conference on Big Data, Dec 2019, Los-Angeles, United States
Conference papers
lirmm-02364411v1
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Parallel Streaming Implementation of Online Time Series Correlation Discovery on Sliding Windows with Regression CapabilitiesCLOSER 2019 - 9th International Conference on Cloud Computing and Services Science, May 2019, Heraklion, Greece. pp.681-687, ⟨10.5220/0007843806810687⟩
Conference papers
lirmm-02265729v1
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Distributed Algorithms to Find Similar Time SeriesECML-PKDD 2019 - European Conference on Machine Learning and Knowledge Discovery in Databases, Sep 2019, Wurtzbourg, Germany. pp.781-785, ⟨10.1007/978-3-030-46133-1_51⟩
Conference papers
lirmm-02265726v1
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Dirichlet Process Mixture Models made Scalable and Effective by means of Massive DistributionSAC 2019 - 34th ACM/SIGAPP Symposium on Applied Computing, Apr 2019, Limassol, Cyprus. pp.502-509, ⟨10.1145/3297280.3297327⟩
Conference papers
hal-01999453v1
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Apprentissage de la pensée informatique : de la formation des enseignant·e·s à la formation de tou·te·s les citoyen·ne·sEIAH Wokshop 2019 - Apprentissage de la pensée informatique de la maternelle à l’Université : retours d’expériences et passage à l’échelle, Jun 2019, Paris, France
Conference papers
hal-02145480v1
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Discovering Tight Space-Time SequencesDaWaK: Data Warehousing and Knowledge Discovery, Sep 2018, Regensburg, Germany. pp.247-257, ⟨10.1007/978-3-319-98539-8_19⟩
Conference papers
hal-01925965v1
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Maximally Informative k-Itemset Mining from Massively Distributed Data StreamsSAC: Symposium on Applied Computing, Apr 2018, Pau, France. pp.502-509, ⟨10.1145/3167132.3167187⟩
Conference papers
hal-01711990v1
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Scientific Data Analysis Using Data-Intensive Scalable Computing: the SciDISC ProjectLADaS: Latin America Data Science Workshop, Aug 2018, Rio de Janeiro, Brazil
Conference papers
lirmm-01867804v1
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Spark-parSketch: A Massively Distributed Indexing of Time Series DatasetsCIKM 2018 - 27th ACM International Conference on Information and Knowledge Management, Oct 2018, Turin, Italy. pp.1951-1954, ⟨10.1145/3269206.3269226⟩
Conference papers
lirmm-01886760v1
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A Distributed Collaborative Filtering Algorithm Using Multiple Data SourcesDBKDA: Advances in Databases, Knowledge, and Data Applications, May 2018, Nice, France
Conference papers
hal-01911684v1
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Massively Distributed Environments and Closed Itemset Mining: The DCIM ApproachCAiSE: Advanced Information Systems Engineering, Jun 2017, Essen, Germany. pp.231-246, ⟨10.1007/978-3-319-59536-8_15⟩
Conference papers
lirmm-01620238v1
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Massively Distributed Environments and Closed Itemset Mining: The DCIM ApproachBDA: Gestion de Données — Principes, Technologies et Applications, Nov 2017, Nancy, France. pp.1-15
Conference papers
lirmm-01620354v1
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RadiusSketch: Massively Distributed Indexing of Time SeriesIEEE International Conference on Data Science and Advanced Analytics (DSAA 2017), Oct 2017, Tokyo, Japan. pp.262-271, ⟨10.1109/DSAA.2017.49⟩
Conference papers
lirmm-01620154v1
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DPiSAX: Massively Distributed Partitioned iSAXICDM 2017 - 17th IEEE International Conference on Data Mining, Nov 2017, New Orleans, LA, United States. pp.1135-1140, ⟨10.1109/ICDM.2017.151⟩
Conference papers
lirmm-01620125v1
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A New Privacy-Preserving Solution for Clustering Massively Distributed Personal Times-SeriesICDE: International Conference on Data Engineering, May 2016, Helsinki, Finland. pp.1370-1373, ⟨10.1109/ICDE.2016.7498347⟩
Conference papers
lirmm-01270268v1
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Mining Maximally Informative k-Itemsets in Massively Distributed EnvironmentsBDA: Gestion de Données — Principes, Technologies et Applications, Nov 2016, Poitiers, France
Conference papers
lirmm-01411190v1
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When sharing computer science with everyone also helps avoiding digital prejudicesSCRATCH, Aug 2015, Amsterdam, Netherlands
Conference papers
hal-01154767v1
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Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series ClusteringSIGMOD: International Conference on Management of Data, May 2015, Melbourne, Australia. pp.779-794, ⟨10.1145/2723372.2749453⟩
Conference papers
hal-01136686v1
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Optimizing the Data-Process Relationship for Fast Mining of Frequent Itemsets in MapReduceMLDM 2015 - 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, Jul 2015, Hamburg, Germany. pp.217-231, ⟨10.1007/978-3-319-21024-7_15⟩
Conference papers
lirmm-01171555v1
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Aggregation-Aware Compression of Probabilistic Streaming Time SeriesMLDM: Machine Learning and Data Mining, Jul 2015, Hamburg, Germany. pp.232-247, ⟨10.1007/978-3-319-21024-7_16⟩
Conference papers
lirmm-01162366v1
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Fast Parallel Mining of Maximally Informative k-Itemsets in Big DataICDM 2015 - 15th IEEE International Conference on Data Mining, Aug 2015, Atlantic City, NJ, United States. pp.359-368, ⟨10.1109/ICDM.2015.86⟩
Conference papers
lirmm-01187275v1
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Data Partitioning for Fast Mining of Frequent Itemsets in Massively Distributed EnvironmentsDEXA 2015 - 26th International Conference on Database and Expert Systems Applications, Sep 2015, Valencia, Spain. pp.303-318, ⟨10.1007/978-3-319-22849-5_21⟩
Conference papers
lirmm-01169603v1
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A Prime Number Based Approach for Closed Frequent Itemset Mining in Big DataDEXA 2015 - 26th International Conference on Database and Expert Systems Applications, Sep 2015, Valencia, Spain. pp.509-516, ⟨10.1007/978-3-319-22849-5_35⟩
Conference papers
lirmm-01169606v1
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Compression de flux de données probabilistes attentive à l'agrégationBDA: Gestion de Données — Principes, Technologies et Applications, Oct 2014, Autrans, France
Conference papers
lirmm-01091870v1
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Fast and Exact Mining of Probabilistic Data StreamsECML PKDD 2013 - Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Sep 2013, Prague, Czech Republic. pp.493-508, ⟨10.1007/978-3-642-40988-2_32⟩
Conference papers
lirmm-00838618v1
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Mining frequent itemsets over tuple-evolving data streamsSAC: Symposium on Applied Computing, Mar 2013, Coimbra, Portugal. pp.267-274, ⟨10.1145/2480362.2480419⟩
Conference papers
lirmm-00830923v1
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A Density-Based Backward Approach to Isolate Rare Events in Large-Scale ApplicationsDS: Discovery Science, Oct 2013, Singapore, Singapore. pp.249-264, ⟨10.1007/978-3-642-40897-7_17⟩
Conference papers
lirmm-00907893v1
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FMU: Fast Mining of Probabilistic Frequent Itemsets in Uncertain Data StreamsBDA 2012 - 28e journées Bases de Données Avancées, Oct 2012, Clermont-Ferrand, France
Conference papers
lirmm-00748605v1
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Discovering Highly Informative Feature Set Over High DimensionsICTAI: International Conference on Tools with Artificial Intelligence, Nov 2012, Athens, Greece. pp.1059-1064, ⟨10.1109/ICTAI.2012.149⟩
Conference papers
lirmm-00753807v1
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Modeling and Clustering Users with Evolving Profiles in Usage StreamsTIME'2012: 19th International Symposium on Temporal Representation and Reasoning, Sep 2012, United Kingdom. pp.133-140
Conference papers
lirmm-00753791v1
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Découverte de motifs d'évolution significatifs dans les séries temporelles d'images satellitesEGC: Extraction et Gestion des Connaissances, Jan 2011, Brest, France. pp.665-676
Conference papers
hal-00640214v1
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A Fast Approximation Strategy for Summarizing a Set of Streaming Time SeriesACM Symposium on Applied Computing, Mar 2010, Sierre, Switzerland
Conference papers
inria-00461781v1
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Extraction d'itemsets distinctifs dans les flux de donnéesExtraction et gestion des connaissances, Jan 2010, France. pp.187-198
Conference papers
hal-00504877v1
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ABS: The Anti Bouncing Model for Usage Data StreamsICDM 2010 - 10th IEEE International Conference on Data Mining, Dec 2010, Sydney, NSW, Australia. pp.1169-1174, ⟨10.1109/ICDM.2010.91⟩
Conference papers
lirmm-00653732v1
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REGLO: une nouvelle stratégie pour résumer un flux de séries temporellesExtraction et Gestion des Connaissances, Jan 2010, Hammamet, Tunisie
Conference papers
inria-00461834v1
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Collaborative Outlier Mining for Intrusion DetectionEGC: Extraction et Gestion des Connaissances, Jan 2009, Strasbourg, France. pp.313-323
Conference papers
lirmm-00345574v1
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SAX: A Privacy Preserving General Purpose Method applied to Detection of IntrusionsACM First International Workshop on Privacy and Anonymity for Very Large Datasets, join with CIKM 09, Nov 2009, Hong Kong, China. pp.17-24
Conference papers
lirmm-00430646v1
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Détection d'enregistrements atypiques dans un flot de données: une approche multi-résolutionExtraction et Gestion des Connaissances, Jan 2009, Strasbourg, France
Conference papers
inria-00461838v1
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Online and Adaptive anomaly Detection: detecting intrusions in unlabelled audit data streamsEGC 2009, 2009, Strasbourg, France
Conference papers
inria-00460723v1
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A Multi-Resolution Approach for Atypical Behaviour MiningPacific-Asia Conference on Knowledge Discovery and Data Mining, Apr 2009, Bangkok, Thailand. pp.899-906, ⟨10.1007/978-3-642-01307-2⟩
Conference papers
inria-00461831v1
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A General Framework for Adaptive and Online Detection of Web attacks18th International World Wide Web Conference - WWW 2009, Apr 2009, Madrid, Spain
Conference papers
inria-00461391v1
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Parameterless Outlier Detection in Data StreamsACM symposium on Applied Computing, Mar 2009, Honolulu, United States. pp.1491-1495
Conference papers
inria-00461827v1
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Détection d'intrusions dans un environnement collaboratif sécuriséEGC: Extraction et Gestion des Connaissances, Jan 2009, Strasbourg, France. pp.301-312
Conference papers
lirmm-00345566v1
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Data Mining for Intrusion Detection: from Outliers to True IntrusionsPAKDD 2009 - 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Apr 2009, Bankok, Thailand. pp.891-898, ⟨10.1007/978-3-642-01307-2_93⟩
Conference papers
inria-00359206v2
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Gradual Trends in Fuzzy Sequential PatternsIPMU: Information Processing and Management of Uncertainty in Knowledge-Based Systems, Jun 2008, Malaga, Spain. pp.456-463
Conference papers
lirmm-00273910v1
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Des séquences aux tendancesINFORSID: INFormatique des ORganisations et Systèmes d’Information et de Décision, May 2008, Fontainebleau, France
Conference papers
lirmm-00273920v1
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Real Time Web Usage Mining with a Distributed Navigation AnalysisRIDE'02: International Workshop on Research Issues on Data Engineering, San Jose, USA, pp.6
Conference papers
lirmm-00268631v1
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TED and EVA : Expressing Temporal Tendencies Among Quantitative Variables Using Fuzzy Sequential PatternsWCCI4: World Congress on Computational Intelligence, Jun 2008, Hong Kong, China. pp.1861-1868, ⟨10.1109/FUZZY.2008.4630623⟩
Conference papers
lirmm-00273907v1
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Time Aware Mining of ItemsetsTIME, Jun 2008, Montreal, Canada. pp.93-97, ⟨10.1109/TIME.2008.12⟩
Conference papers
inria-00359182v1
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Limites d'une approche incrémentale pour la segmentation de séquences dans les fluxFouille de données complexes dans un processus d'extraction de connaissances, Jan 2007, Namur, Belgique
Conference papers
inria-00461878v1
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Classification de flots de séquences basée sur une approche centroïdeFouille de données complexes dans un processus d'extraction de connaissances, Jan 2006, Lille, France. pp.131-139
Conference papers
inria-00461880v1
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Classification de flots de séquences basée sur une approche centroïdeINFORSID, Informatique des organisations et systèmes d'information et de décision, Jun 2006, Hammamet, Tunisie
Conference papers
inria-00461839v1
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Extraction de motifs séquentiels dans les flots de données d'usage du WebExtraction et Gestion des Connaissances, Jan 2006, Lille, France. pp.627-638
Conference papers
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Peer-to-Peer Usage Analysis: a Distributed Mining Approach AINA: Advanced Information Networking and Applications, 2006, Vienna, Austria
Conference papers
hal-00106798v1
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Web Usage Mining : extraction de périodes denses à partir des logsEGC: Extraction et Gestion des Connaissances, Jan 2006, Lille, France. pp.403-408
Conference papers
inria-00461840v1
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Mining Sequential Patterns from Temporal Streaming DataFirst ECML/PKDD Workshop on Mining Spatio-Temporal Data (MSTD'05), held in conjunction with the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'05), Nov 2005, Porto, Portugal
Conference papers
inria-00461843v1
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Mining Data Streams for Frequent Sequences ExtractionIEEE first Workshop on Mining Complex Data (MCD'05). Held in conjunction with ICDM'05, Nov 2005, Houston, United States
Conference papers
inria-00461876v1
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Web Usage Mining: Extracting Unexpected Periods from Web LogsIEEE 2nd Workshop on Temporal Data Mining (TDM'05). Held in conjunction with ICDM'05, Nov 2005, Houston, United States
Conference papers
inria-00461877v1
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Web Usage Mining: Sequential Pattern Extraction with a Very Low SupportAdvanced Web Technologies and Applications: 6th Asia-Pacific Web Conference, APWeb 2004, Apr 2004, Hangzhou, China. pp.513--522, ⟨10.1007/978-3-540-24655-8_56⟩
Conference papers
hal-00950768v1
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Pre-Processing Time Constraints for Efficiently Mining Generalized Sequential PatternsTIME'04: 11th International Symposium on Temporal Representation and Reasoning, Jul 2004, Tatihou, Basse-Normandie (France), France. pp.87-95, ⟨10.1109/TIME.2004.1314424⟩
Conference papers
lirmm-00108888v1
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HDM, un Module de Fouille de Données Distribué et Temps RéelEGC: Extraction et Gestion des Connaissances, Jan 2002, Montpellier, France. pp.393-398
Conference papers
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Web Usage Mining: How to Efficiently Manage New Transactions and New ClientsPKDD 2000 - 4th European Conference on Principles of Data Mining and Knowledge Discovery, Sep 2000, Lyon, France. pp.530-535, ⟨10.1007/3-540-45372-5_62⟩
Conference papers
hal-00008926v1
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Highly Scalable Real-Time Analytics with CloudDBApplianceXLDB: Extremely Large Databases Conference, Oct 2017, Clermont-Ferrand, France. , 10th Extremely Large Databases Conference, 2017
Conference poster
lirmm-01632355v1
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Successes and New Directions in Data MiningIDEA Group, pp.1-369, 2007, 13 978-1599046457
Books
lirmm-00365422v1
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Data Mining Patterns: New Methods and ApplicationsIDEA Group, pp.307, 2007, 13 978-1599041629
Books
lirmm-00365419v1
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Variable-Size Segmentation for Time Series RepresentationTransactions on Large-Scale Data- and Knowledge-Centered Systems LIII, 13840, pp.34-65, 2023, Lecture Notes in Computer Science, 978-3-662-66862-7. ⟨10.1007/978-3-662-66863-4_2⟩
Book sections
lirmm-03882927v1
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Anomaly Detection in Time SeriesTransactions on Large-Scale Data- and Knowledge-Centered Systems L, LNCS. TLDKS -12930, , pp.46-62, 2021, Lecture Notes in Computer Science. Transactions on Large-Scale Data- and Knowledge-Centered Systems, 978-3-662-64553-6. ⟨10.1007/978-3-662-64553-6_3⟩
Book sections
lirmm-03359500v1
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Mining Common Outliers for Intrusion DetectionFabrice Guillet; Gilbert Ritschard; Djamel Abdelkader Zighed; Henri Briand. Advances in Knowledge Discovery and Management, 292, Springer, pp.217-234, 2010, Studies in Computational Intelligence, 978-3-642-00579-4. ⟨10.1007/978-3-642-00580-0_13⟩
Book sections
lirmm-00798705v1
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Intrusion Detections in Collaborative Organizations by Preserving PrivacyFabrice Guillet and Gilbert Ritschard and Djamel Abdelkader Zighed and Henri Briand. Advances in Knowledge Discovery and Management, 292, Springer, pp.235-247, 2010, Studies in Computational Intelligence, 978-3-642-00579-4. ⟨10.1007/978-3-642-00580-0_14⟩
Book sections
lirmm-00430642v1
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Web Usage Mining for Ontology ManagementData Mining with Ontologies: Implementation, Findings and Framework, Idea Group Publishing, pp.37-64, 2007
Book sections
hal-00256574v1
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Sequential Pattern MiningJohn Wang. Encyclopedia of Data Warehousing and Mining, Idea Group Reference, pp.1028-1032, 2005, 1-59140-557-2
Book sections
lirmm-00106576v1
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Procédé et installation de comparaison de consommation d'effluents sans divulgation de données de consommations mesuréesFrance, N° de brevet: EP 2930471 A1. 2015
Patents
hal-01274207v1
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Process for identifying rare eventsUnited States, Patent n° : EP13153512A; EP2014051963W. 2013
Patents
lirmm-00913008v1
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« Structures : organisation, complexité, dynamique » des mot-clés au sens inattendu2015
Other publications
hal-01238442v1
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Isolating rare events in large-scale applications using a backward approach[Research Report] RR-13003, LIRMM. 2013
Reports
lirmm-00798074v1
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Médiation Scientifique : une facette de nos métiers de la recherche[Interne] Inria. 2013, pp.34
Reports
hal-00804915v1
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Extraction de connaissances : réunir volumes de données et motifs significatifsBase de données [cs.DB]. Université Nice Sophia Antipolis, 2009
Habilitation à diriger des recherches
tel-00788309v1
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